A 42-page framework for taking AI-visibility measurement from side-project to operating rhythm. This is the executive summary, the key concepts, the data model, and the three chapters most customers reference when operationalizing GEO inside their marketing org.
Chapter 1, The data model
Five primitives: brand, prompt, engine, answer, mention. The paper defines each precisely, shows how they relate as a relational model, and walks through the twelve derived metrics that fall out, from raw mention frequency to weighted share of voice to rolling sentiment drift. Understanding the primitives is what separates teams that use dashboards coherently from teams that argue about what the numbers mean.
Chapter 2, The scoring rubric
Visibility, position, sentiment, citation-trust, and competitor-diff, each scored on a published scale with calibration checks documented publicly. This is the chapter most frequently referenced in customers' own internal documentation when presenting to stakeholders who want to know how the number works and whether they can trust it.
Chapter 3, Cadence and cross-functional ownership
Who owns the dashboard. When alerts fire. How the weekly review meeting runs. What an end-of-quarter executive summary looks like. Includes three org-chart diagrams from real Promptive customers showing how GEO monitoring was embedded across brand, demand gen, and SEO teams. The most practically useful chapter in the paper.
Download the full PDF for the complete framework, the scoring worksheet your team can complete in a single 90-minute session, and the twelve-week implementation timeline for operationalizing GEO measurement from zero.
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